Deep learning for smart home security systems: CNN-based home security

被引:0
|
作者
Balasubramanian, M. [1 ]
Kakade, Kiran Shrimant [2 ]
Mane, Sulakshana B. [3 ]
Anand, Sujatha Jamuna [4 ]
机构
[1] SA Engn Coll, Dept Comp Sci & Engn, Chennai, Tamil Nadu, India
[2] World Peace Univ, Fac Business & Leadership, MIT, Pune, India
[3] Bharati Vidyapeeth Coll Engn, Navi Mumbai, India
[4] Loyola Inst Technol, Dept Elect & Commun Engn, Chennai, India
关键词
deep learning; smart home; IoT; RL; RECOGNITION; STATE; ART;
D O I
10.1504/IJESDF.2024.139652
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
A smart home enables new modes of connection and the consumption of various services. Additionally, AI and deep learning have aided in the enhancement of many services and jobs by making them more automated. In this study, we used IoT and deep learning to create a safe and efficient home automation system. Using deep learning approach, the user is able to operate appliances such as fans, televisions, bulbs, and other electronic or electrical equipment by either speaking commands into their mobile device or using an application that is pre-installed on their mobile device. The results of the trials that were carried out demonstrate that the suggested deep learning model is more accurate than the KNN method, and that the RL system improves the user's quality of experience by as much as 3.8 points on a scale of 10.
引用
收藏
页码:451 / 463
页数:14
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